The proposed project has the overall goal of developing methods and tools to optimize three-dimensional planning of radiation therapy of cancer. Techniques will be developed for optimization of beam directions. To facilitate this, the algorithms for automatic beam generation and for automatic designing of the beam apertures will be implemented. The optimization algorithm will be refined to allow finding the optimal beam directions in a few minutes on a modem workstation. Beam directions and beam weights will be optimized simultaneously. Techniques for designing optimal beam cross-section intensities will be developed. The approaches that will be investigated are: partial framing of the target volume to exclude organs at risk obscuring the target volume, and calculating the optimal beam compensator by back-projecting the dose calculational points. New types of scoring functions will be developed to include not only objective measures of the plan but also planner's subjective preferences, intuition and experience. The overall score functions including various aspects of treatment will be investigated. Biological models for estimating tumor control and normal tissue complication probabilities will be used. Tools will be developed for clinical assessment of computer optimized plans. This will include a user-friendly "point and click" type interface, including spreadsheets, protocols and tools for comparing rival plans using the quantitative measures and subjective opinions of experienced clinicians. Techniques for speeding-up the laborious process of delineating organs of interest on many (CT, MR) slices used for 3D planning and optimization will be developed. Automatic and semi-automatic feature extraction will be investigated using deformable models to describe organs and elastic deformation algorithms to fit the organ models to the anatomic structures in a particular patient's images. The optimization techniques and tools will be developed on a programming platform which provides an ongoing support for patient treatment. The results of this research will be applied to clinical cases to judge their efficacy. It is expected that the outcome of the proposed research will make the optimization of three-dimensional treatment plans a compelling part of routine treatment planning and in consequence, will improve the quality of cancer treatment.